EVENT : C3BI Seminars – Methodological
Network biology approaches to uncover the mechanisms of Salmonella infection and its autophagy modulating features in the gut
Speaker : Tamas Korcsmaros, Research Leader from TGAC, The Genome Analysis Centre, Norwich Research Park, Norwich, UK – Institute of Food Research, Norwich Research Park, Norwich, UK Time : 02:00 pm Starting Date : 07/12/2015
Location : Retrovirus room – LWOFF (22), Institut Pasteur, Paris
In the last decade, networks became a novel approach in understanding how changes in cellular processes can lead to diseases, such as cancer, infection and inflammatory bowel disease (IBD). In our studies we focus on autophagy (cellular self-degradation) and its regulation. Autophagy is a stress response mechanism also important in development, immune regulation, ageing and cancer, where it could act as both pro- and anti-tumorigenic. Autophagy malfunction is also known to be related to IBD, and it is often manipulated by intestinal pathogenic bacteria, such as Salmonella.To investigate how Salmonella is modulating autophagy we developed the first large-scale network resource for Salmonella enterica, integrating known and predicted regulatory, metabolic and signalling interactions. We investigated the variation and commonality in the networks of Salmonella serovars with either a predominantly intestinal or extra-intestinal pathogenicity. We analysed the differences (e.g., regulatory connections) for 10 strains of two niche groups (intestinal / extraintestinal), as well as defined a “core” Salmonella consensus network. Then, built on the combination of earlier identified Salmonella-host interactions and our recently published Autophagy Regulatory Network resource (http://autophagy-regulation.org), we predicted novel genes responsible for autophagy modulation in the gut using the intestine specific Salmonella networks. Finally, we have designed a fluorescence reporter system to monitor autophagy of Salmonella and to validate the role of predicted genes. The developed bioinformatics workflows and experimental validation system could be used for other strains or pathogens to iteratively predict genes for biological validation with the potential to provide additional insight or model refinement.
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